---
base_model: klue/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: cosmetic3_roberta
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# cosmetic3_roberta

This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3549
- Accuracy: 0.8520
- F1: 0.8563
- Precision: 0.8640
- Recall: 0.8526

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4186        | 1.0   | 277  | 0.2708          | 0.8877   | 0.8911 | 0.8933    | 0.8897 |
| 0.3237        | 2.0   | 554  | 0.4175          | 0.8623   | 0.8624 | 0.8755    | 0.8727 |
| 0.2054        | 3.0   | 831  | 0.4479          | 0.8986   | 0.9008 | 0.9087    | 0.9055 |
| 0.3151        | 4.0   | 1108 | 0.3885          | 0.9130   | 0.9154 | 0.9163    | 0.9173 |
| 0.1832        | 5.0   | 1385 | 0.4418          | 0.9094   | 0.9120 | 0.9122    | 0.9132 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2